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Record W7132919981

Right to Read and Play: How are Ontario Kindergarten Educators Currently Integrating Alphabetics into Play-Based Learning?

2023· dissertation· W7132919981 on OpenAlexaffabout
Ruxandra Filip

Bibliographic record

VenueTSpace · 2023
Typedissertation
Language
FieldSocial Sciences
TopicChild Development and Digital Technology
Canadian institutionsOntario College of Art and Design
Fundersnot available
KeywordsPhonemic awarenessFluencyLiteracyContext (archaeology)Early literacyPhonicsPhonological awarenessReading (process)Comprehension
DOInot available

Abstract

fetched live from OpenAlex

Learning to read involves the development of many skills, including alphabetics, fluency, and comprehension. Alphabetics are the foundation of early reading and serve as precursors to the development of fluency and comprehension skills. Research evidence has accumulated in support of the direct instruction of alphabetics; however, direct instruction is sometimes perceived to be in opposition to constructivist approaches such as play-based learning. This study examined how Ontario Kindergarten teachers integrated the teaching of alphabetics within the context of a play-based learning curriculum. Observational video data collected across 21 demographically diverse kindergarten classrooms in Ontario were deductively coded for type of alphabetics and instructional approach. Results demonstrate that educators use both direct instruction and teacher-facilitated play to support students’ development of early literacy skills (e.g., phonological awareness, phonemic awareness, alphabet knowledge, and phonics). The results suggest that developmentally appropriate literacy instruction in kindergarten can include both direct instruction and teacher-facilitated play.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.585
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.019
GPT teacher head0.330
Teacher spread0.311 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designQualitative
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2023
Admission routes2
Has abstractyes

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